KR102295670B1 - Hub terminal candidate area selection method - Google Patents

Abstract

Arrays including {departure point, plurality of waypoints, destination point} for a plurality of parcels are obtained from the parcel DB in which the transportation routes of parcels that were actually transported are stored, and two different ones of the arrays are obtained. After inputting the arrays into a common path search algorithm, and outputting a string in which points included in the common path of the two different arrays are sequentially connected, the output string is parsed into individual points, and the counted individual points The method of selecting candidate areas for the hub terminal is disclosed by displaying them on the map.

Description

Hub terminal candidate area selection method

The present invention relates to a method for selecting a candidate hub terminal area.

Courier companies have regional hub terminals through which deliveries across the country pass. In general, the courier delivery service may cause economic disadvantages in terms of time and cost if the delivery route is set incorrectly. Nevertheless, according to the existing delivery logistics systems for each courier company, delivery is often carried out along a route several times longer than the optimal route between the delivery origin and the delivery destination. Therefore, the location of the hub terminal, ie, logistics, needs to be adjusted so that the moving distance of courier delivery can be reduced.

An object of the present invention is to provide a method for selecting a candidate area for a hub terminal that can reduce the moving distance of a courier delivery in a delivery moving path in order to solve the above-described problem.

A hub terminal candidate area selection method according to an aspect of the present invention is {departure point, plurality of transit points, destination point} for a plurality of parcels from a parcel DB in which transportation routes of parcels that were actually transported are stored. obtaining arrays comprising inputting two different arrays from among the arrays into a common path search algorithm, and outputting a string in which points included in the common path of the two different arrays are sequentially connected; parsing the output string into individual points; and counting the individual points and displaying them on a map.

In this case, the performing of the common path search algorithm may include: generating a matrix having the number of points included in each of the two arrays as row and column lengths; initializing the matrix; When each character string of the first array of the two arrays is sequentially compared with each character string of the second array of the two arrays and has the same value, the same value is added to the component value of the current matrix position of the matrix storing a string concatenated with values in a position of a next matrix element; and outputting a string in which points included in a common path of the first array and the second array, which are component values of the last matrix position of the matrix, are sequentially connected.

In this case, the step of obtaining the arrays including {the starting point, the plurality of waypoints, the destination point} may include obtaining a plurality of detailed waypoints based on the plurality of waypoints.

In this case, the step of acquiring the arrays is configured to further acquire information on latitude and longitude for each point among the movement paths of the plurality of parcels, and when counting the individual points and displaying them on a map, the latitude and hardness.

In this case, the method may further include selecting a point having the largest value excluding the existing hub terminal from among the values displayed on the map as a hub terminal candidate area.

According to an aspect of the present invention, a computing device including a processing unit may be provided. In the computing device, the processing unit obtains arrays including {start point, a plurality of stopover points, destination point} for a plurality of parcels from a parcel DB in which transportation routes of parcels that were actually transported are stored. to do; inputting two different arrays from among the arrays into a common path search algorithm, and outputting a string in which points included in the common path of the two different arrays are sequentially connected; parsing the output string into individual points; and counting the individual points and displaying them on a map.

In this case, the performing of the common path search algorithm may include: generating a matrix having the number of points included in each of the two arrays as row and column lengths; initializing the matrix; When each character string of the first array of the two arrays is sequentially compared with each character string of the second array of the two arrays and has the same value, the same value is added to the component value of the current matrix position of the matrix storing a string concatenated with values in a position of a next matrix element; and outputting a string in which points included in a common path of the first array and the second array, which are component values of the last matrix position of the matrix, are sequentially connected.

According to an aspect of the present invention, it is possible to provide a computer-readable non-tray storage medium in which a program including command codes for selecting a candidate hub terminal area is recorded by a computer device. The computer-readable non-transitory recording medium, when the command codes are executed, causes the computer device to store a obtaining arrays including a departure point, a plurality of waypoints, and a destination point}; inputting two different arrays from among the arrays into a common path search algorithm, and outputting a string in which points included in the common path of the two different arrays are sequentially connected; parsing the output string into individual points; and counting the individual points and displaying them on a map.

In this case, the performing of the common path search algorithm may include: generating a matrix having the number of points included in each of the two arrays as row and column lengths; initializing the matrix; When each character string of the first array of the two arrays is sequentially compared with each character string of the second array of the two arrays and has the same value, the same value is added to the component value of the current matrix position of the matrix storing a string concatenated with values in a position of a next matrix element; and outputting a string in which points included in a common path of the first array and the second array, which are component values of the last matrix position of the matrix, are sequentially connected.

According to the present invention, it is possible to provide a method for selecting a candidate area for a hub terminal that can reduce the moving distance of a courier delivery in a delivery moving path.

1A is a diagram for explaining a relationship between a computing device and a courier DB in which the steps of selecting a candidate hub terminal area to be described later are performed according to an embodiment of the present invention, and FIG. Data on transport routes are presented in a table.
Figure 2 shows detailed transportation routes for the courier goods (A, B, C) according to an embodiment of the present invention.
3 shows an LCRS algorithm according to an embodiment of the present invention.
4A and 4B show a matrix to which an LCRS algorithm according to an embodiment of the present invention is applied.
5 shows a table in which common points are parsed for each comparison path according to an embodiment of the present invention.
6 is a view showing points that have passed many times on the moving path of actual courier goods according to an embodiment of the present invention.
7 is a flowchart for explaining each step of a method for selecting a candidate area for a hub terminal according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, the present invention is not limited to the embodiments described herein and may be implemented in various other forms. The terminology used in this specification is intended to help the understanding of the embodiments, and is not intended to limit the scope of the present invention. Also, singular forms used hereinafter include plural forms unless the phrases clearly indicate the opposite.

1A is a diagram for explaining a relationship between a computing device and a courier DB in which the steps of selecting a candidate hub terminal area, which will be described later, are performed according to an embodiment of the present invention, and FIG. Data on transport routes are presented in a table.

The computing device 10 may include a communication unit 11 , a data collection unit 12 , a processing unit 13 , a storage unit 14 , and .

The communication unit 11 may communicate with the courier DB 20 . Through the communication unit 11, {invoice number, product category, departure point, a plurality of stopover points, destination point, latitude, longitude} pairs for a plurality of parcels may be acquired. In this case, the acquired information may be transmitted to the data collection unit 12 .

The processing unit 13 may perform the steps of selecting a candidate hub terminal area, which will be described later.

The storage unit 14 may store information acquired through the communication unit 11 and information processed by the processing unit 13 .

The courier DB 20 may store information on the invoice number of each parcel delivery product, information on the sender, information on the recipient, product category, origin, stopover points, and destination, and the like.

Each field of the table of FIG. 1b may include information obtained from the courier DB, such as invoice number, product category, branch visit order, branch name, latitude and longitude.

For example, the first parcel delivery product (A) is assigned an invoice number (Path1) and belongs to the category of home appliances. A4), and the third waypoint A6 can be moved to the destination point A7. In this case, the latitude and longitude of the departure point A1 may be latA1 and longA1, and the latitude and longitude of the arrival point A7 may be latA7 and longA7.

The second courier product (B) is assigned an invoice number (Path2) and belongs to the clothing category, starting from the departure point (B1), the first waypoint (B3), the second waypoint (B5), and It may be moved to the destination point B9 via the third waypoint B7. In this case, the latitude and longitude of the departure point B1 may be latB1 and longB1, and the latitude and longitude of the arrival point B9 may be latB9 and longB9.

In this way, including {departure point, a plurality of transit points, destination point} for a plurality of courier goods from the courier DB in which the transportation routes of the parcels (A, B, ...) that were actually transported are stored arrays can be obtained.

Figure 2 shows detailed transportation routes for the courier goods (A, B, C) according to an embodiment of the present invention.

3 illustrates a Longest Common Route Subsequence (LCRS) algorithm (ie, a common route search algorithm) according to an embodiment of the present invention.

4A and 4B show a matrix to which an LCRS algorithm according to an embodiment of the present invention is applied.

Hereinafter, it will be described with reference to FIGS. 2 and 4B together.

The first path Path1 may include {a starting point A1, a plurality of detailed waypoints A2 to A6, and a destination point A7}. That is, the first array for the first path Path1 may be represented by {A1, A2, A3, A4, A5, A6, A7}.

The second path Path2 may include {a starting point B1, a plurality of detailed waypoints B2 to B8, and a destination point B9}. That is, the second array for the second path Path2 may be expressed as {B1, B2, B3, B4, B5, B6, B7, B8, B9}.

The third path Path3 may include {a starting point C1, a plurality of detailed waypoints C2 to C7, and a destination point C8}. That is, the third array for the third path Path3 may be represented by {C1, C2, C3, C4, C5, C6, C7}.

When detailed transportation routes for the parcels A, B, and C are determined, two different combinations of the respective transportation routes Path1, Path2, and Path3 may be input to the common route search algorithm. For example, the first array of the first path Path1 and the second array of the second path Path2 may be input to the common path search algorithm.

When the first array and the second array are input to a common path search algorithm, the length of the first array (eg, 7) and the length of the second array (eg, 9) are the length of the row and the length of the column. You can create a matrix (lcrs[][]). For example, the generated matrix may be initialized with a "" character as shown in FIG. 4A.

At this time, by comparing the respective values of the first array and the second array, the value (A[p]) of the first array of a specific sequence number (p) and the value of the specific sequence number (q) of the second array (B[p) ]), the value (A[p]) of the specific sequence number of the first array is connected to the current value (lcrs[p][q]) of the LCRS matrix to lcrs[p+1][q+1] can be stored in

At this time, if the value (A[p]) of the specific sequence number (p) of the first array (B[p]) is different from the value (B[p]) of the specific sequence number (q) of the second array, lcrs[p+1][q+ 1] may be stored as the larger of the lcrs[p][q+1] value and the lcrs[p+1][q] value.

_{In the last component (lcrs 68} ) of the LCRS matrix to which the common path search algorithm is applied, a string in which points included in the common path of the first array and the second array are sequentially connected may be stored. For example, as shown in Figure 4b, LCRS ₆₈ = s1s2s3 may be.

In this way, the output string (LCRS last matrix component value) can be obtained by applying the common path search algorithm to all pairs of arrays.

The output string may be parsed into individual points as shown in FIG. 5 .

5 shows a table in which common points are parsed for each comparison path according to an embodiment of the present invention.

The table may consist of fields of a first comparison path name, a second comparison path name, an index, and a common point name.

In this case, the index may mean the number of the common point. That is, it may be a value indicating the number of common points among the total number of common points.

For example, the first common point of the first comparison path Path1 and the second comparison path Path2 may be s1, the second common point may be s2, and the third common point may be s3. In addition, the first common point of the second comparison path Path2 and the third comparison path Path3 may be s2, the second common point may be s3, and the third common point may be s4.

After the output string is parsed into individual points as shown in FIG. 5, each individual point (ie, common point) can be counted. For example, in three paths, it can be seen that the number of times s1 is included in the common point is 1, the number of times s2 is included is 3, the number of times s3 is included is 3, and the number of times s4 is included is 1.

The counted points may be displayed on the map as shown in FIG. 6 .

6 is a view showing points that have passed many times on the moving path of actual courier goods according to an embodiment of the present invention.

Figure 6 (a) shows a map that visualizes the routes of all data sets of the delivery DB, and Figure 6 (b) is each of the actual routes with respect to the valid data (10%) of all the data sets of the delivery DB. It shows a map showing the location of the points using latitude and longitude, and (c) of FIG. 6 shows a visualized map of the points extracted and counted through the common route search algorithm (LCRS algorithm), as shown in FIG. d) is a visualization of the counting result.

At this time, in the case of (b) and (c) of Fig. 6, the darker the color of the circle, the greater the number of overlapping visits, and in the case of Fig. 6 (d), the larger the size of the circle, the greater the number of final visits. do.

Referring to (d) of FIG. 6 , it can be seen that although there are few locations with a large number of common visits in Seoul, there is a logistical volume at very various points. In other words, it can be seen that Seoul has the largest distribution volume. Second, it can be seen that there is a large amount of logistics at the branch corresponding to the Okcheon hub. And third, it can be seen that there is a large amount of logistics in the Busan area.

Also, considering that the large circle exists in the area corresponding to the Gyeongbu Expressway, the Seoul and Busan branches have the highest demand for parcel delivery, and the Okcheon Hub, the largest logistics hub in Korea between Seoul and Busan, has a common number of visits. You can find out the most

Therefore, for example, a hub terminal candidate region replacing the Okcheon hub may be determined as the region having the highest number of common visits. That is, a point corresponding to the second largest circle after the Okcheon hub and having the minimum time and distance can be selected as a hub terminal candidate area.

7 is a flowchart for explaining each step of a method for selecting a candidate area for a hub terminal according to an embodiment of the present invention.

In step S10, arrays including {departure point, plurality of stopover points, destination point} for a plurality of parcels can be obtained from a parcel DB in which transportation routes of parcels that were actually transported are stored. .

In step S20, two different arrays among the arrays may be input to a common path search algorithm to output a string in which points included in the common path of the two different arrays are sequentially connected.

In step S30, the output string may be parsed into individual points.

In step S40, the individual points may be counted and displayed on the map as the size of a circle. In this case, in another embodiment, the counting number of individual points may be displayed in a method other than the size of the circle.

In step S50, a point having the largest circle excluding the current hub terminal among circles displayed on the map may be selected as a hub terminal candidate area.

By using the above-described embodiments of the present invention, those skilled in the art will be able to easily implement various changes and modifications within the scope without departing from the essential characteristics of the present invention. The content of each claim in the claims may be combined with other claims without reference within the scope that can be understood through this specification.

This patent application is supported by the following research project.

(1) Host institution: Hongik University Industry-University Cooperation Foundation

(2) Assignment number:

Applicant organization: 2019R1F1A1056123

School: 201901200001

(3) Supporting institution: National Research Foundation of Korea

(4) Principal Investigator: Department of Information and Computer Engineering, College of Engineering

(5) Title: Professor

(6) Name: Song Ha-yoon

(7) Title of research project: Data science platform including meta-machine learning for efficient analysis of data collected from Internet of Things equipment -Focused on geolocation information-

(8) Project name: Basic research project in science and engineering field (general researcher-basic)

(9) Total research period: 2019.6.1. ~ 2022.2.28. (2.75 years)

(10) The study period: 2019.6.1. ~ 2020.2.29. (0.75 years)

(11) Total research expenses: 137,500,000 won

(12) Current research grant: KRW 37,500,000

Claims (9)

obtaining, by the computing device, arrays including {departure point, plurality of waypoints, destination point} for a plurality of parcels from a parcel DB in which transportation routes of parcels that were actually transported are stored;
outputting, by the computing device, a string in which points included in a common path of the two different arrays are sequentially connected by inputting, by the computing device, two different arrays among the arrays to a common path search algorithm;
parsing, by the computing device, the output string into individual points; and
counting, by the computing device, the individual points and displaying them on a map;
containing,
How to select candidate areas for Hub Terminal. According to claim 1,
The performing step of the common path search algorithm is,
generating, by the computing device, a matrix having the number of points included in each of the two arrays as the lengths of rows and columns;
initializing, by the computing device, the matrix;
When the computing device sequentially compares each character string in a first array of the two arrays with each character string in a second array of the two arrays to have the same value, the position of the current matrix of the matrix is storing a string obtained by concatenating the same value to a component value in a position of a next matrix component; and
outputting, by the computing device, a string in which points included in a common path of the first array and the second array, which are component values of the last matrix position of the matrix, are sequentially connected;
containing,
How to select candidate areas for Hub Terminal. The method according to claim 1, wherein the obtaining of the arrays including {start point, a plurality of waypoints, a destination point} comprises obtaining a plurality of detailed waypoints based on the plurality of waypoints. How to select candidate areas for Hub Terminal. According to claim 1,
The step of acquiring the arrays is to further acquire information on latitude and longitude for each point among the moving paths of the plurality of parcels,
The individual points are counted and displayed using the latitude and longitude when displayed on the map,
How to select candidate areas for Hub Terminal. The method of claim 1, further comprising the step of selecting, by the computing device, a point having a largest value excluding an existing hub terminal from among the values displayed on the map as a hub terminal candidate area. . A computing device comprising a processing unit, comprising:
The processing unit,
obtaining arrays including {departure point, plurality of stopover points, destination point} for a plurality of delivery articles from a delivery DB in which transport routes of delivery goods that were actually transported are stored;
inputting two different arrays from among the arrays into a common path search algorithm, and outputting a string in which points included in the common path of the two different arrays are sequentially connected;
parsing the output string into individual points; and
counting the individual points and displaying them on a map;
intended to perform
computing device. 7. The method of claim 6,
The performing step of the common path search algorithm is,
generating a matrix having the number of points included in each of the two arrays as the lengths of rows and columns;
initializing the matrix;
When each character string of the first array of the two arrays is sequentially compared with each character string of the second array of the two arrays and has the same value, the same value is added to the component value of the current matrix position of the matrix storing a string concatenated with values in a position of a next matrix element; and
outputting a string in which points included in a common path of the first array and the second array, which are component values of the last matrix position of the matrix, are sequentially connected;
containing,
computing device. As a computer-readable non-transitory recording medium in which a program including command codes for selecting a hub terminal candidate area is recorded by a computer device,
When the instruction codes are executed, cause the computer device to:
obtaining arrays including {departure point, plurality of stopover points, destination point} for a plurality of delivery articles from a delivery DB in which transport routes of delivery goods that were actually transported are stored;
inputting two different arrays from among the arrays into a common path search algorithm, and outputting a string in which points included in the common path of the two different arrays are sequentially connected;
parsing the output string into individual points; and
counting the individual points and displaying them on a map;
characterized in that it is adapted to perform
A computer-readable non-transitory recording medium. 9. The method of claim 8,
The performing step of the common path search algorithm is,
generating a matrix having the number of points included in each of the two arrays as the lengths of rows and columns;
initializing the matrix;
When each character string of the first array of the two arrays is sequentially compared with each character string of the second array of the two arrays and has the same value, the same value is added to the component value of the current matrix position of the matrix storing a string concatenated with values in a position of a next matrix element; and
outputting a string in which points included in a common path of the first array and the second array, which are component values of the last matrix position of the matrix, are sequentially connected;
containing,
A computer-readable non-transitory recording medium.

Images